{
 "metadata": {
  "name": "",
  "signature": "sha256:59163e6a7ce6cae25ec9d3478ae8a1c060718dc5694e5ae1100681bbd49ee94b"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "from sklearn.datasets import make_circles"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 176
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "X, y = make_circles(n_samples=1000, factor=0.5, noise=.01)\n",
      "plt.scatter(X[:, 0], X[:, 1], c=y);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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kZQPi16/hft4FeHt6cjEsjIt+friQ9YCaiPAfA6YBnyDuonbufViRC8S3blu+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\nGo1G42Bo4ddoNBoH4/8BsORWo8yKwP0AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x109225518>"
       ]
      }
     ],
     "prompt_number": 211
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "np.max(np.arange(-3, 3), 0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 212,
       "text": [
        "2"
       ]
      }
     ],
     "prompt_number": 212
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.base import BaseEstimator, TransformerMixin\n",
      "from sklearn.utils import check_random_state\n",
      "\n",
      "def inplace_relu(X):\n",
      "    X[X < 0] = 0\n",
      "    return X\n",
      "\n",
      "\n",
      "def get_activation(name):\n",
      "    if name is None:\n",
      "        return lambda x: x\n",
      "    elif name == 'tanh':\n",
      "        return np.tanh\n",
      "    elif name == 'relu':\n",
      "        return inplace_relu\n",
      "    else:\n",
      "        raise ValueError(\"unknown activation: \" + name)\n",
      "\n",
      "\n",
      "class RandomEmbedder(BaseEstimator, TransformerMixin):\n",
      "    \n",
      "    def __init__(self, n_components=100, random_state=None, activation=\"tanh\"):\n",
      "        self.n_components = n_components\n",
      "        self.random_state = random_state\n",
      "        self.activation = activation\n",
      "\n",
      "    def fit(self, X, y=None):\n",
      "        n_samples, n_features = X.shape\n",
      "        rng = check_random_state(self.random_state)\n",
      "        self.components_ = rng.normal(size=(self.n_components, n_features))\n",
      "        return self\n",
      "\n",
      "    def transform(self, X, y=None):\n",
      "        X_projected = np.dot(X, self.components_.T)\n",
      "        return get_activation(self.activation)(X_projected)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 307
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "embedder = RandomEmbedder(n_components=2, activation=\"relu\", random_state=0)\n",
      "X_1 = embedder.fit_transform(X)\n",
      "plt.scatter(X_1[:, 0], X_1[:, 1], c=y);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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4XMjSSEPgLDAZaI7ZvI277/6i4LWDBz+FzWbl66+/IyTExogRS6lbt+71PwlF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\n5ZXisDrNenCKBbs4QJISk9S+zFdsRITYjIZyqs5sFrc4LBZ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       "text": [
        "<matplotlib.figure.Figure at 0x108c27828>"
       ]
      }
     ],
     "prompt_number": 308
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "embedder = RandomEmbedder(n_components=2, activation=\"tanh\", random_state=0)\n",
      "X_1 = embedder.fit_transform(X)\n",
      "plt.scatter(X_1[:, 0], X_1[:, 1], c=y);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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bvF6OAcmVz0FiySHALiQTZyySdw/SF2dVQADjxo9n1CjJ21mzfn3FKl/NOXv2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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x108363a20>"
       ]
      }
     ],
     "prompt_number": 309
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.pipeline import Pipeline\n",
      "\n",
      "activation = \"relu\"\n",
      "\n",
      "p = Pipeline([\n",
      "    (\"rnd\", RandomEmbedder(n_components=10, activation=activation)),\n",
      "    (\"rnd2\", RandomEmbedder(n_components=10, activation=activation)),\n",
      "    (\"rnd3\", RandomEmbedder(n_components=10, activation=activation)),\n",
      "    (\"out\", RandomEmbedder(n_components=2, activation=None)),\n",
      "])\n",
      "X_2 = p.fit_transform(X)\n",
      "plt.scatter(X_2[:, 0], X_2[:, 1], c=y);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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qKy0tjTGjRzPC51PbqCLMWLoUpbyPo3K/xAFzUEo9GKczlccee/SsvtxuN7/9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\n5oIgCF6AiLkgCIIX8P9NfK/418wKxAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x108c13860>"
       ]
      }
     ],
     "prompt_number": 404
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.base import BaseEstimator, TransformerMixin\n",
      "from sklearn.linear_model import RidgeCV\n",
      "from sklearn.utils import check_random_state\n",
      "\n",
      "\n",
      "class AEELMTransformer(BaseEstimator, TransformerMixin):\n",
      "    \n",
      "    def __init__(self, n_components=100, activation='tanh',\n",
      "                 alphas=np.logspace(-3, 3, 7), random_state=None):\n",
      "        self.n_components = n_components\n",
      "        self.alphas = alphas\n",
      "        self.random_state = random_state\n",
      "        self.activation = activation\n",
      "\n",
      "    def fit(self, X, y=None):\n",
      "        n_samples, n_features = X.shape\n",
      "        rng = check_random_state(self.random_state)\n",
      "        rnd_proj = rng.normal(size=(n_features, self.n_components))\n",
      "        X_proj = get_activation(self.activation)(np.dot(X, rnd_proj))\n",
      "        \n",
      "        self.ridge_ = ridge = RidgeCV(alphas=self.alphas)\n",
      "        ridge.fit(X_proj, X)\n",
      "        \n",
      "        self.components_ = ridge.coef_.T\n",
      "        return self\n",
      "        \n",
      "    def transform(self, X, y=None):\n",
      "        projected = np.dot(X, self.components_.T)\n",
      "        return get_activation(self.activation)(projected)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 312
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.pipeline import Pipeline\n",
      "\n",
      "activation = 'relu'\n",
      "p = Pipeline([\n",
      "    (\"aeelm\", AEELMTransformer(n_components=10, activation=activation)),\n",
      "    (\"aeelm2\", AEELMTransformer(n_components=10, activation=activation)),\n",
      "    (\"aeelm3\", AEELMTransformer(n_components=10, activation=activation)),\n",
      "    (\"out\", RandomEmbedder(n_components=2, activation=None)),\n",
      "])\n",
      "X_3 = p.fit_transform(X)\n",
      "plt.scatter(X_3[:, 0], X_3[:, 1], c=y);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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SM2bMwGazlfv53DgBfOX6moiXl5E2bdp4OCbl76jkryhu2LRpM3agiD8KIAzk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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x108c200b8>"
       ]
      }
     ],
     "prompt_number": 437
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def shuffle_columns(X, copy=True, seed=None):\n",
      "    rng = np.random.RandomState(seed)\n",
      "    if copy:\n",
      "        X = X.copy()\n",
      "    for i in range(X.shape[1]):\n",
      "        rng.shuffle(X[:, i])\n",
      "    return X\n",
      "\n",
      "\n",
      "def make_membership_pbm(X, seed=None):\n",
      "    rng = np.random.RandomState(seed)\n",
      "    n_samples, n_features = X.shape\n",
      "    shuffle_idx = rng.permutation(2 * n_samples)\n",
      "    \n",
      "    X = np.vstack([X, shuffle_columns(X, seed=seed)])\n",
      "    y = np.concatenate([np.ones(n_samples), -np.ones(n_samples)])\n",
      "    return X[shuffle_idx], y[shuffle_idx]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 314
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}